The Standardized S-X 2 Statistic for Assessing Item Fit.

The S-X 2 statistic (Orlando & Thissen, 2000) is popular among researchers and practitioners who are interested in the assessment of item fit. However, the statistic suffers from the Chernoff-Lehmann problem (Chernoff & Lehmann, 1954) and hence does not have a known asymptotic null distribution. This paper suggests a modified version of the S-X 2 statistic that is based on the modified Rao-Robson χ 2 statistic (Rao & Robson, 1974). A simulation study and a real data analyses demonstrate that the use of the modified statistic instead of the S-X 2 statistic would lead to fewer items being flagged for misfit.

Microbial mechanism of zinc fertilizer input on rice grain yield and zinc content of polished rice.

Zinc is an essential minor element for rice growth and human health, which can also change the structure of the microorganisms. However, it remains unclear for the effects of zinc fertilizer on microbiome function in agricultural soils and crops. To solve this research gap, we investigated the relationship between improving rice (Oryza sativa L.) yield, Zn concentration, soil microbial community diversity, and function by the application of Zn fertilizer. The field trials included three rice varieties (Huanghuazhan, Nanjing9108, and Nuodao-9925) and two soil Zn levels (0 and 30 kg ha-1) in Jiangsu province, China. As a test, we studied the variety of soil bacterial composition, diversity, and function using 16S rRNA gene sequencing. The results showed that soil Zn application reduced the diversity of microbial community, but the bacterial network was more closely linked, and the metabolic function of bacterial community was improved, which increased the grain yield (17.34-19.52%) and enriched the Zn content of polished rice (1.40-20.05%). Specifically, redundancy analysis (RDA) and Mantel's test results revealed soil total nitrogen (TN) was the primary driver that led to a community shift in the rice rhizosphere bacterial community, and soil organic carbon (SOC) was considered to have a strong influence on dominant phyla. Furthermore, network analysis indicated the most critical bacterial taxa were identified as Actinobacteria, Bacteroidetes, Proteobacteria, and Chloroflexi based on their topological roles of microorganisms. KEGG metabolic pathway prediction demonstrated that soil Zn application significantly (p < 0.05) improved lipid metabolism, amino acid metabolism, carbohydrate metabolism, and xenobiotic biodegradation. Overall, their positive effects were different among rice varieties, of which Nanjing-9108 (NJ9108) performed better. This study opens new avenues to deeply understand the plant and soil-microbe interactions by the application of fertilizer and further navigates the development of Zn-rich rice cultivation strategies.

Microbial ingress and in vitro degradation enhanced by glucose on bioabsorbable Mg-Li-Ca alloy.

Biodegradable magnesium alloys are challenging to be implanted in patients with hyperglycemia and diabetes. A hypothesis is suggested that glucose accelerates microbial ingress and in vitro degradation of Mg-Li-Ca implants. Corrosion resistance and mechanical properties was demonstrated using electrochemical, hydrogen evolution and tensile tests. The bacteria from Hank's solution were isolated via 16S rRNA gene analysis. The results revealed that Mg-1Li-1Ca alloy exhibited different responses to Hank's solution with and without glucose. The solution acidity was ascribed to Microbacterium hominis and Enterobacter xiangfangensis, indicating that glucose promoted microbial activity and degradation and deterioration in mechanical property of Mg-1Li-1Ca alloy.

Predictive Feature Generation and Selection Using Process Data From PISA Interactive Problem-Solving Items: An Application of Random Forests.

The Programme for International Student Assessment (PISA) introduced the measurement of problem-solving skills in the 2012 cycle. The items in this new domain employ scenario-based environments in terms of students interacting with computers. Process data collected from log files are a record of students' interactions with the testing platform. This study suggests a two-stage approach for generating features from process data and selecting the features that predict students' responses using a released problem-solving item-the Climate Control Task. The primary objectives of the study are (1) introducing an approach for generating features from the process data and using them to predict the response to this item, and (2) finding out which features have the most predictive value. To achieve these goals, a tree-based ensemble method, the random forest algorithm, is used to explore the association between response data and predictive features. Also, features can be ranked by importance in terms of predictive performance. This study can be considered as providing an alternative way to analyze process data having a pedagogical purpose.

Corrosion resistance and antibacterial properties of polysiloxane modified layer-by-layer assembled self-healing coating on magnesium alloy.

Magnesium (Mg) alloys have shown great potential in biomedical materials due to their biocompatibility and biodegradability. However, rapid corrosion rate, which is an inevitable obstacle, hinders their clinical applications. Besides, it is necessary to endow Mg alloys with antibacterial properties, which are crucial for temporary implants. In this study, silver nanoparticles (AgNPs) and polymethyltrimethoxysilane (PMTMS) were introduced into AZ31 Mg alloys via layer-by-layer (LbL) assembly and siloxane self-condensation reaction. The characteristics of the composite films were investigated by SEM, UV-vis, FT-IR, and XRD measurements. Corrosion resistance of the samples was measured by electrochemical and hydrogen evolution tests. Antibacterial activities of the films against Staphylococcus aureus were evaluated by plate-counting method. The results demonstrated that the composite film with smooth and uniform morphologies could enhance the corrosion resistance of Mg alloys owing to the physical barrier and the self-healing functionality of polysiloxane. Moreover, the composite coating possessed antibacterial properties and could prolong the release of assembled silver ions.

The UMP Exact Test and the Confidence Interval for Person Parameters in IRT Models.

In educational and psychological measurement when short test forms are used, the asymptotic normality of the maximum likelihood estimator of the person parameter of item response models does not hold. As a result, hypothesis tests or confidence intervals of the person parameter based on the normal distribution are likely to be problematic. Inferences based on the exact distribution, on the other hand, do not suffer from this limitation. However, the computation involved for the exact distribution approach is often prohibitively expensive. In this paper, we propose a general framework for constructing hypothesis tests and confidence intervals for IRT models within the exponential family based on exact distribution. In addition, an efficient branch and bound algorithm for calculating the exact p value is introduced. The type-I error rate and statistical power of the proposed exact test as well as the coverage rate and the lengths of the associated confidence interval are examined through a simulation. We also demonstrate its practical use by analyzing three real data sets.